On Using Gaussian Mixture Model for Double-Talk Detection in Acoustic Echo Suppression

被引：0

作者：

Song, Ji-Hyun ^{[1
]}

Lee, Kyu-Ho ^{[1
]}

Park, Yun-Sik ^{[1
]}

Kang, Sang-Ick ^{[1
]}

Chang, Joon-Hyuk ^{[1
]}

机构：

[1] Inha Univ, Sch Elect Engn, Inchon, South Korea

来源：

11TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2010 (INTERSPEECH 2010), VOLS 3 AND 4 | 2010年

关键词：

Voice Activity Detection; Second-order Conditional MAP; Soft Decision; Likelihood Ratio Test;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, we propose a novel frequency-domain approach to double-talk detection (DTD) based on the Gaussian mixture model (GMM). In contrast to a previous approach based on a simple and heuristic decision rule utilizing time-domain cross-correlations, GMM is applied to a set of feature vectors extracted from the frequency-domain cross-correlation coefficients. Performance of the proposed approach is evaluated through objective tests under various environments, and better results are obtained as compared to the time-domain method.

引用

页码：2782 / 2785

页数：4

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